This book continues where DOE Simplified leaves off in Chapter 8 with an introduction to "Response Surface Methods [RSM] for Optimization." It presents this advanced tool for design of experiments (DOE) in a way that anyone with a minimum of technical training can understand and appreciate. Unlike any other book of its kind, RSM Simplified keeps formulas to a minimum—making liberal use of figures, charts, graphs and checklists. It also offers many relevant examples, amusing and fun do-it-yourself exercises.

RSM Simplified keeps formulas to a minimum and makes liberal use of figures, charts, graphs and checklists. It offers many relevant examples, with amusing sidebars and do-it-yourself exercises that will lead readers to the peak potential for their product quality and process efficiency. The authors, Mark J. Anderson and Patrick J. Whitcomb, are principals of Stat-Ease, a provider of DOE training, consulting, and software. They both are professional chemical engineers. Anderson has more of a business background while Whitcomb specializes in statistics. Incorporated into this book is the more advanced Design-Expert, version 7 software for Windows, with a 180-day trial, so the reader can do the complex statistical computations, generate the necessary graphics (2D and 3D maps) and perform the numerical optimization.

"This is an engaging and informative book on the modern practice of experimental design. The authors' writing style is entertaining, the consulting dialogs are extremely enjoyable, and the technical material is presented brilliantly but not overwhelmingly. The book is a joy to read. Everyone who practices or teaches DOE should read this book." - Douglas C. Montgomery, Regents Professor, Department of Industrial Engineering, Arizona State University "It's been said: 'Design for the experiment, don't experiment for the design.' This book ably demonstrates this notion by showing how tailor-made, optimal designs can be effectively employed to meet a client's actual needs. It should be required reading for anyone interested in using the design of experiments in industrial settings." —Christopher J. Nachtsheim, Frank A Donaldson Chair in Operations Management, Carlson School of Management, University of Minnesota This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities? While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain.

Offering a planned approach for determining cause and effect, DOE Simplified: Practical Tools for Effective Experimentation, Third Edition integrates the authors decades of combined experience in providing training, consulting, and computational tools to industrial experimenters. Supplying readers with the statistical means to analyze how numerous variables interact, it is ideal for those seeking breakthroughs in product quality and process efficiency via systematic experimentation.Following in the footsteps of its bestselling predecessors, this edition incorporates a lively approach to learning the fundamentals of the design of experiments (DOE). It lightens up the inherently dry complexities with interesting sidebars and amusing anecdotes.The book explains simple methods for collecting and displaying data and presents comparative experiments for testing hypotheses. Discussing how to block the sources of variation from your analysis, it looks at two-level factorial designs and covers analysis of variance. It also details a four-step planning process for designing and executing experiments that takes statistical power into consideration.This edition includes a major revision of the software that accompanies the book (via download) and sets the stage for introducing experiment designs where the randomization of one or more hard-to-change factors can be restricted. Along these lines, it includes a new chapter on split plots and adds coverage of a number of recent developments in the design and analysis of experiments.Readers have access to case studies, problems, practice experiments, a glossary of terms, and a glossary of statistical symbols, as well as a series of dynamic online lectures that cover the first several chapters of the book.

Many chemists – especially those most brilliant in their field – fail to appreciate the power of planned experimentation. They dislike the mathematical aspects of statistical analysis. In addition, these otherwise very capable chemists also dismissed predictive models based only on empirical data. Ironically, in the hands of subject matter experts like these elite chemists, the statistical methods of mixture design and analysis provide the means for rapidly converging on optimal compositions. What differentiates Formulation Simplified from the standard statistical texts on mixture design is that the authors make the topic relatively easy and fun to read. They provide a whole new collection of insighful original studies that illustrate the essentials of mixture design and analysis. Solid industrial examples are offered as problems at the end of many chapters for those who are serious about trying new tools on their own. Statistical software to do the computations can be freely accessed via a web site developed in support of this book.

Our rationale for the second edition remains the same as for the first edition, which appeared over twenty years ago. This is to offer simplified, useful and easily understood methods for dealing with the creep of components operating under conditions met in practice. When the first edition was written, we could not claim that the methods which were introduced were well-tried. They were somewhat conjectural, although firmly based, but not sufficiently well devel oped. Since that time, the Reference Stress Methods (RSM) introduced in the book have received much scrutiny and development. The best recognition we could have of the original methods is the fact that they are now firmly embedded in codes of practice. Hopefully, we have now gone a long way towards achieving our original objectives. There are major additions to this second edition which should help to justify our claims. These include further clarification regarding Reference Stress Methods in Chapter 4. There are also new topics which depend on RSM in varying degrees: • Creep fracture is covered in Chapter 7, where methods for assessing creep crack initiation and crack growth are fully described. This chapter starts with a review of the basic concepts of fracture mechanics and follows with useful, approximate methods, compatible with the needs of design for creep and the availability of standard data. • Creep/fatigue interactions and environmental effects appear in Chapter 8.

The most comprehensive, single-volume guide to conductingexperiments with mixtures "If one is involved, or heavily interested, in experiments onmixtures of ingredients, one must obtain this book. It is, as wasthe first edition, the definitive work." -Short Book Reviews (Publication of the International StatisticalInstitute) "The text contains many examples with worked solutions and with itsextensive coverage of the subject matter will prove invaluable tothose in the industrial and educational sectors whose work involvesthe design and analysis of mixture experiments." -Journal of the Royal Statistical Society "The author has done a great job in presenting the vitalinformation on experiments with mixtures in a lucid and readablestyle. . . . A very informative, interesting, and useful book on animportant statistical topic." -Zentralblatt fur Mathematik und Ihre Grenzgebiete Experiments with Mixtures shows researchers and students how todesign and set up mixture experiments, then analyze the data anddraw inferences from the results. Virtually every technique thathas appeared in the literature of mixtures can be found here, andcomputing formulas for each method are provided with completelyworked examples. Almost all of the numerical examples are takenfrom real experiments. Coverage begins with Scheffe latticedesigns, introducing the use of independent variables, and endswith the most current methods. New material includes: * Multiple response cases * Residuals and least-squares estimates * Categories of components: Mixtures of mixtures * Fixed as well as variable values for the major componentproportions * Leverage and the Hat Matrix * Fitting a slack-variable model * Estimating components of variances in a mixed model using ANOVAtable entries * Clarification of blocking mates and choice of mates * Optimizing several responses simultaneously * Biplots for multiple responses